A Study of MAP Estimation Techniques for Nonlinear Filtering
Paper in proceedings, 2012

For solving the nonlinear filtering problem, much attention has been paid to filters based on the Linear Minimum Mean Square Error (LMMSE) estimation. Accordingly, less attention has been paid to MAP estimation techniques in this field. We argue that, given the superior performance of the latter in certain situations, they deserve to be more carefully investigated. In this paper, we look at MAP estimation from optimization perspective. We present a new method that uses this technique for solving the nonlinear filtering problem and we take a look at two existing methods. Furthermore, we derive a new method to reduce the dimensionality of the optimization problem which helps decreasing the computational complexity of the algorithms. The performance of MAP estimation techniques is analyzed and compared to LMMSE filters. The results show that in the case of informative measurements, MAP estimation techniques have much better performance.

MAP estimation

Progressive Correction

LMMSE Estimation

Nonlinear Filtering

Author

Maryam Fatemi

Chalmers, Signals and Systems, Signalbehandling och medicinsk teknik, Signal Processing

Lennart Svensson

Chalmers, Signals and Systems, Signalbehandling och medicinsk teknik, Signal Processing

Lars Hammarstrand

Chalmers, Signals and Systems, Signalbehandling och medicinsk teknik, Signal Processing

Mark Morelande

15th international conference on information fusion, July 09-12 2012, Singapore

1058 - 1065

Areas of Advance

Information and Communication Technology

Subject Categories

Signal Processing

ISBN

978-1-4673-0417-7

More information

Created

10/7/2017